Boosting SARS-CoV-2 detection combining pooling and multiplex strategies
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Abstract
RT-qPCR is the gold standard technique available for SARS-CoV-2 detection. However, the long test run time and costs associated with this type of molecular testing are a challenge in a pandemic scenario. Due to high testing demand, especially for monitoring highly vaccinated populations facing the emergence of new SARS-CoV-2 variants, strategies that allow the increase in testing capacity and cost savings are needed. We evaluated a RT-qPCR pooling strategy either as a simplex and multiplex assay, as well as performed in-silico statistical modeling analysis validated with specimen samples obtained from a mass testing program of Industry Federation of the State of Rio de Janeiro (Brazil). Although the sensitivity reduction in samples pooled with 32 individuals in a simplex assay was observed, the high-test sensitivity was maintained even when 16 and 8 samples were pooled. This data was validated with the results obtained in our mass testing program with a cost saving of 51.5% already considering the expenditures with pool sampling that were analyzed individually. We also demonstrated that the pooling approach using 4 or 8 samples tested with a triplex combination in RT-qPCR is feasible to be applied without sensitivity loss, mainly combining Nucleocapsid (N) and Envelope (E) gene targets. Our data shows that the combination of pooling in a RT-qPCR multiplex assay could strongly contribute to mass testing programs with high-cost savings and low-reagent consumption while maintaining test sensitivity. In addition, the test capacity is predicted to be considerably increased which is fundamental for the control of the virus spread in the actual pandemic scenario.
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SciScore for 10.1101/2020.08.16.20167536: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement IACUC: For the pooling validation, we used leftovers from routine testing samples, and no personal, clinical, and demographic data from individuals were accessed, therefore the institutional ethics committee (CEP/HUCFF/FM/UFRJ) waived the informed consent term for this study.
IRB: All methods and experimental protocols were approved and carried out in accordance with guidelines and regulations from the institutional committee.Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
Software and Algorithms Sentences Resources The nasopharyngeal swabs were conditioned in DMEM medium … SciScore for 10.1101/2020.08.16.20167536: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement IACUC: For the pooling validation, we used leftovers from routine testing samples, and no personal, clinical, and demographic data from individuals were accessed, therefore the institutional ethics committee (CEP/HUCFF/FM/UFRJ) waived the informed consent term for this study.
IRB: All methods and experimental protocols were approved and carried out in accordance with guidelines and regulations from the institutional committee.Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
Software and Algorithms Sentences Resources The nasopharyngeal swabs were conditioned in DMEM medium (Thermofisher), and 1.5 mL of each sample were individually stored at -80°C in cryotubes until further use. Thermofishersuggested: (ThermoFisher; SL 8; Centrifuge, RRID:SCR_020809)Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:This way, pooling samples may be an interesting approach to overcome these limitations and provide access to mass testing. One of the main concerns of pooling is the size of assembled pools that should be evaluated according to the prevalence of the pathogen in the study population. Some studies have demonstrated that for diseases with low population prevalence, this approach has the most potential for enabling mass testing at low costs, including for SARS-CoV-2 detection10,15. Besides, it was seen a great potential of pooling for repeat testing of the same population on a consecutive period, which could be an efficient strategy for disease control16. However, the prediction of ideal pool size (Table 1) requires a discerning in silico analysis. Otherwise, the cost-saving will not be reached. Mathematically, applying the Dorfman’s approaches may incur savings as high as 90% within populations with a prevalence close to 1%. Our study adopted the statistical modeling approach and validated the data with pooling biological samples for COVID-19 diagnostic, confirming that the pool size must be selected according to the prevalence rate of positive cases in the population (Figure 2). Besides, this combined analysis is essential to allow the optimization of limited resources and to apply mass testing enabling the management and reduction of underreporting, observed globally, but especially in large and developing countries17,18. For SARS-CoV-2 detection, other published studies perfo...
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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